Senior ML Backend Engineer – Search & Recommendations

• Build and run query and recommendation serving: retrieval, score fusion, filtering, and caching
• Maintain double-digit-millisecond p95 latency for search-as-you-type
• Design graceful degradation for slow or unavailable models and vector paths
• Build experiment plumbing including shadow traffic, A/B assignment, guardrail metrics, and rollback
• Build change-data-capture from source systems into search indexes and feature stores with measured freshness
• Keep embeddings fresh for new and updated items
• Run zero-downtime reindexing of multi-million-document collections
• Build feature logging that turns production traffic into training data for ranking models
• Ship changes into product teams' backends and clients, including new endpoints, cutovers, and experiment flags
• Work with product engineering teams on reviews, release windows, and production ownership
• Provide monitoring, alerting, runbooks, and on-call support for shipped systems
• Collaborate with search data scientists and the ranking lead on search and recommendation serving

• 5+ years building backend or platform systems in production
• 2+ years operating a production search engine (Elasticsearch, OpenSearch, Solr, Typesense, Vespa or similar): index lifecycle, analyzers, reindexing at scale, debugging relevance issues with data scientists
• Low-latency services under real traffic, and the ability to explain where the p95 goes
• Streaming ingestion: Kafka, Debezium or similar change-data-capture, plus idempotent backfills
• Strong Python
• Comfortable shipping in TypeScript
• Shipped changes through A/B tests and staged rollouts
• Daily use of agentic coding tools such as Claude Code